fitModeShift: Fit model in which the mode of trait evolution shifts once

In paleoTS: Analyze Paleontological Time-Series

Fit model in which the mode of trait evolution shifts once

Description

Trait evolution is modeled as a shift from a random walk (general or unbiased) to stasis, or vice versa.

Usage

fitModeShift(
  y,
  minb = 7,
  pool = TRUE,
  order = c("Stasis-RW", "RW-Stasis"),
  rw.model = c("URW", "GRW"),
  method = c("Joint", "AD"),
  silent = FALSE,
  hess = FALSE,
  ...
)

Arguments

y	paleoTS object
minb	minimum number of populations within each segment
pool	if TRUE, sample variances are substituted with their pooled estimate
order	whether stasis or random walk come first, one of Stasis-RW or RW-Stasis
rw.model	whether the random walk segment is an unbiased random walk, URW or a general random walk, GRW
method	parameterization to use: Joint or AD
silent	logical, if TRUE, progress updates are suppressed
hess	if TRUE, standard errors computed from the Hessian matrix are returned
...	other arguments, passed to optimization functions

Value

a paleoTSfit object

See Also

sim.Stasis.RW

Examples

x <- sim.Stasis.RW(ns = c(15, 15), omega = 0.5, ms = 1, order = "Stasis-RW")
plot(x)
w <- fitModeShift(x, order = "Stasis-RW", rw.model = "GRW")
abline(v = x$tt[15], lwd = 3)  # actual shift point
abline(v = x$tt[w$par["shift1"]], lty = 3, lwd = 2, col = "red") # inferred shift

paleoTS documentation built on Aug. 9, 2022, 1:06 a.m.